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Liu RL, Wang T, Yao YL, Lv XY, Hu YL, Chen XZ, Tang XJ, Zhong ZH, Fu LJ, Luo X, Geng LH, Yu SM, Ding YB. Association of ambient air pollutant mixtures with IVF/ICSI-ET clinical pregnancy rates during critical exposure periods. Hum Reprod Open 2024; 2024:hoae051. [PMID: 39301245 PMCID: PMC11412601 DOI: 10.1093/hropen/hoae051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 08/04/2024] [Indexed: 09/22/2024] Open
Abstract
STUDY QUESTION Does exposure to a mixture of ambient air pollutants during specific exposure periods influence clinical pregnancy rates in women undergoing IVF/ICSI-embryo transfer (ET) cycles? SUMMARY ANSWER The specific exposure period from ET to the serum hCG test was identified as a critical exposure window as exposure to sulfur dioxide (SO2) or a combination of air pollutants was associated with a decreased likelihood of clinical pregnancy. WHAT IS KNOWN ALREADY Exposure to a single pollutant may impact pregnancy outcomes in women undergoing ART. However, in daily life, individuals often encounter mixed pollution, and limited research exists on the effects of mixed air pollutants and the specific exposure periods. STUDY DESIGN SIZE DURATION This retrospective cohort study involved infertile patients who underwent their initial IVF/ICSI-ET cycle at an assisted reproduction center between January 2020 and January 2023. Exclusions were applied for patients meeting specific criteria, such as no fresh ET, incomplete clinical and address information, residency outside the 17 cities in the Sichuan Basin, age over 45 years, use of donor semen, thin endometrium (<8 mm) and infertility factors unrelated to tubal or ovulation issues. In total, 5208 individuals were included in the study. PARTICIPANTS/MATERIALS SETTING METHODS Daily average levels of six air pollutants (fine particulate matter (PM2.5), inhalable particulate matter (PM10), SO2, nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were acquired from air quality monitoring stations. The cumulative average levels of various pollutants were determined using the inverse distance weighting (IDW) method across four distinct exposure periods (Period 1: 90 days before oocyte retrieval; Period 2: oocyte retrieval to ET; Period 3: ET to serum hCG test; Period 4: 90 days before oocyte retrieval to serum hCG test). Single-pollutant logistic regression, two-pollutant logistic regression, Quantile g-computation (QG-C) regression, and Bayesian kernel machine regression (BKMR) were employed to evaluate the influence of pollutants on clinical pregnancy rates. Stratified analyses were executed to discern potentially vulnerable populations. MAIN RESULTS AND THE ROLE OF CHANCE The clinical pregnancy rate for participants during the study period was 54.53%. Single-pollutant logistic models indicated that for PM2.5 during specific exposure Period 1 (adjusted odds ratio [aOR] = 0.83, 95% CI: 0.70-0.99) and specific exposure Period 4 (aOR = 0.83, 95% CI: 0.69-0.98), and SO2 in specific exposure Period 3 (aOR = 0.92, 95% CI: 0.86-0.99), each interquartile range (IQR) increment exhibited an association with a decreased probability of clinical pregnancy. Consistent results were observed with dual air pollution models. In the multi-pollution analysis, QG-C indicated a 12% reduction in clinical pregnancy rates per IQR increment of mixed pollutants during specific exposure Period 3 (aOR = 0.89, 95% CI: 0.79-0.99). Among these pollutants, SO2 (33.40%) and NO2 (33.40%) contributed the most to the negative effects. The results from BKMR and QG-C were consistent. Stratified analysis revealed increased susceptibility to ambient air pollution among individuals who underwent transfer of two embryos, those with BMI ≥ 24 kg/m2 and those under 35 years old. LIMITATIONS REASONS FOR CAUTION Caution was advised in interpreting the results due to the retrospective nature of the study, which was prone to selection bias from non-random sampling. Smoking and alcohol, known confounding factors in IVF/ICSI-ET, were not accounted for. Only successful cycles that reached the hCG test were included, excluding a few patients who did not reach the ET stage. While IDW was used to estimate pollutant concentrations at residential addresses, data on participants' work locations and activity patterns were not collected, potentially affecting the accuracy of exposure prediction. WIDER IMPLICATIONS OF THE FINDINGS Exposure to a mixture of pollutants, spanning from ET to the serum hCG test (Period 3), appeared to be correlated with a diminished probability of achieving clinical pregnancy. This association suggested a potential impact of mixed pollutants on the interaction between embryos and the endometrium, as well as embryo implantation during this critical stage, potentially contributing to clinical pregnancy failure. This underscored the importance of providing women undergoing ART with comprehensive information to comprehend the potential environmental influences and motivating them to adopt suitable protective measures when feasible, thereby mitigating potential adverse effects of contaminants on reproductive health. STUDY FUNDING/COMPETING INTERESTS This work received support from the National Key Research and Development Program of China (No. 2023YFC2705900), the National Natural Science Foundation of China (Nos. 82171664, 81971391, 82171668), the Natural Science Foundation of Chongqing Municipality of China (Nos. CSTB2022NSCQ-LZX0062, CSTB2023TIAD-KPX0052) and the Foundation of State Key Laboratory of Ultrasound in Medicine and Engineering (No. 2021KFKT013). The authors report no conflicts of interest. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Rui-Ling Liu
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Toxicology, Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Tong Wang
- Department of Toxicology, Key Lab of Medical Protection for Electromagnetic Radiation, Ministry of Education of China, Institute of Toxicology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing, China
| | - Ying-Ling Yao
- Department of Toxicology, Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Xing-Yu Lv
- The Reproductive Center, Sichuan Jinxin Xinan Women & Children's Hospital, Chengdu, Sichuan, China
| | - Yu-Ling Hu
- The Reproductive Center, Sichuan Jinxin Xinan Women & Children's Hospital, Chengdu, Sichuan, China
| | - Xin-Zhen Chen
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Xiao-Jun Tang
- Department of Toxicology, Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Zhao-Hui Zhong
- Department of Toxicology, Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Li-Juan Fu
- Department of Toxicology, Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health, Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
| | - Xin Luo
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li-Hong Geng
- The Reproductive Center, Sichuan Jinxin Xinan Women & Children's Hospital, Chengdu, Sichuan, China
| | - Shao-Min Yu
- Department of Obstetrics and Gynecology, The People's Hospital of Yubei, Chongqing, China
| | - Yu-Bin Ding
- Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Pharmacology, Academician Workstation, Changsha Medical University, Changsha, China
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Xian Y, Zhang Y, Liu Z, Wang H, Xiong T. Characterization of winter PM 2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 947:174557. [PMID: 38977099 DOI: 10.1016/j.scitotenv.2024.174557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 07/04/2024] [Accepted: 07/04/2024] [Indexed: 07/10/2024]
Abstract
In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality-Integrated Source Apportionment Method (CMAQ-ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21-40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> -20 μg/m3) after 2011 due to pollution control measures.
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Affiliation(s)
- Yaohan Xian
- College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China
| | - Yang Zhang
- College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China; Key Laboratory of Atmospheric Environment Simulation and Pollution Control at Chengdu University of Information Technology of Sichuan Province, Chengdu 610225, China; Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225, China.
| | - Zhihong Liu
- College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China; Key Laboratory of Atmospheric Environment Simulation and Pollution Control at Chengdu University of Information Technology of Sichuan Province, Chengdu 610225, China; Chengdu Plain Urban Meteorology and Environment Observation and Research Station of Sichuan Province, Chengdu University of Information Technology, Chengdu 610225, China
| | - Haofan Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Tianxin Xiong
- College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225, China
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Zhang J, Wang R, Chen C, Su Y, Chen L, Zhang W, Xi Y, Yu Y, Pu R, Lu M, Wu R, Shen X. Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:7934-7947. [PMID: 38170362 DOI: 10.1007/s11356-023-31737-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 12/22/2023] [Indexed: 01/05/2024]
Abstract
Carbonaceous particles are an important chemical component of atmospheric fine particles. In this study, a single particle aerosol mass spectrometer was used to continuously measure the carbonaceous particles in Chengdu, one of the megacities most affected by haze in China, from January 22 to March 3, 2021. During the observation period, the average mass concentration of PM2.5 was 62.3 ± 37.2 μg m-3, and the emissions from mobile sources were more prominent. Carbonaceous particles accounted for 68.6% of the total particles and could be classified into 10 categories, with elemental carbon (EC) mixed with sulfate (EC-S) particles making the highest contribution (33.1%). EC particles rich in secondary components and organic carbon (OC) particles rich in secondary component exhibited different diurnal variations, suggesting different sources and mixing mechanisms. From "excellent" to "polluted" days, the contributions of EC-S, EC mixed with sulfate and nitrate (EC-SN) and OC mixed with EC (OC-EC) particles increased by 9.8%, 4.5% and 6.6%, respectively, and thus these particles are key targets for future pollution control. The potential source contribution of the southwest area was stronger than that of other areas, and the potential contribution of regional transport to EC-related particles was stronger than to OC-related particles. Most particles were highly mixed with sulfate or nitrate, and the level of secondary mixing further enhanced as pollution worsened.
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Affiliation(s)
- Junke Zhang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
| | - Rui Wang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Chunying Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Yunfei Su
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Luyao Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Wei Zhang
- Sichuan Ecological Environment Monitoring Station, Chengdu, 610091, China
| | - Yingwei Xi
- Sichuan Ecological Environment Monitoring Station, Chengdu, 610091, China
| | - Yangchun Yu
- Shandong Academy for Environmental Planning, Jinan, 250101, China
| | - Ruiyan Pu
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Minghui Lu
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Ruohan Wu
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Xuhui Shen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
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Huang J, Li X, Zhang Y, Zhai S, Wang W, Zhang T, Yin F, Ma Y. Socio-demographic characteristics and inequality in exposure to PM 2.5: A case study in the Sichuan basin, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120630. [PMID: 36375581 DOI: 10.1016/j.envpol.2022.120630] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 11/07/2022] [Accepted: 11/07/2022] [Indexed: 06/16/2023]
Abstract
The Chengyu Metropolitan Area (CYMA), located in the Sichuan Basin, is an unevenly developed region with high PM2.5 concentrations and a population of approximately 100 million. Although exposure inequality in air pollution has received increasing concern, no related research has been carried out in the CYMA to date. In this work, we used the concentration index to assess inequality of PM2.5 population-weighted exposure in the CYMA among different subgroups, including age, education, gender, occupation and GDP per capita in the city of residence. Our findings revealed that the non-disadvantaged subgroups (people aged 15-64, people with senior and higher education, people with high-income occupations and residents of cities with high GDP per capita) had a higher PM2.5 exposure in the CYMA, with the concentration indices of -0.03 (95% CI: 0.064, -0.001), -0.14 (95% CI: 0.221, -0.059), -0.15 (95% CI: 0.238, -0.056) and -0.27 (95% CI: 0.556, 0.012), opposite to previous studies in developed countries such as the United States and France. In addition, exposure differences among cities were much larger than those among populations in the CYMA. These findings may benefit the government in identifying disproportionately exposed subgroups in developing regions, and suggest that related measures should initially be carried out for cities exposed to high PM2.5 concentrations rather than for populations exposed to high PM2.5 concentrations.
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Affiliation(s)
- Jingfei Huang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xuelin Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Siwei Zhai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China; Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, China.
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Spring 2020 Atmospheric Aerosol Contamination over Kyiv City. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Extraordinarily high aerosol contamination was observed in the atmosphere over the city of Kyiv, Ukraine, during the March–April 2020 period. The source of contamination was the large grass and forest fires in the northern part of Ukraine and the Kyiv region. The level of PM2.5 load was investigated using newly established AirVisual sensor mini-networks in five areas of the city. The aerosol data from the Kyiv AERONET sun-photometer site were analyzed for that period. Aerosol optical depth, Ångström exponent, and the aerosol particles properties (particle size distribution, single-scattering albedo, and complex refractive index) were analyzed using AERONET sun-photometer observations. The smoke particles observed at Kyiv site during the fires in general correspond to aerosol with optical properties of biomass burning aerosol. The variability of the optical properties and chemical composition indicates that the aerosol particles in the smoke plumes over Kyiv city were produced by different burning materials and phases of vegetation fires at different times. The case of enormous PM2.5 aerosol contamination in the Kyiv city reveals the need to implement strong measures for forest fire control and prevention in the Kyiv region, especially in its northwest part, where radioactive contamination from the Chernobyl disaster is still significant.
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Zhang J, Li H, Chen L, Huang X, Zhang W, Zhao R. Particle composition, sources and evolution during the COVID-19 lockdown period in Chengdu, southwest China: Insights from single particle aerosol mass spectrometer data. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2022; 268:118844. [PMID: 34776748 PMCID: PMC8575539 DOI: 10.1016/j.atmosenv.2021.118844] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 06/13/2023]
Abstract
In order to investigate the effects of the Coronavirus Disease 2019 (COVID-19) lockdown on air quality in cities in southwest China, a single particle aerosol mass spectrometer (SPAMS) and other online equipments were used to measure the air pollution in Chengdu, one of the megacities in this area, before and during the lockdown period. It was found that the concentrations of fine particulate matter (PM2.5), nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) decreased by 38.6%, 77.5%, 47.0%, 35.1% and 14.1%, respectively, while the concentration of ozone (O3) increased by 57.5% from the time before to the time during lockdown. All particles collected during the study period could be divided into eight categories: biomass burning (BB), coal combustion (CC), vehicle emissions (VE), cooking emissions (CE), Dust, K-nitrate (K-NO3), K-sulfate (K-SO4) and K-sulfate-nitrate (K-SN) particles, and their contributions changed significantly after the beginning of lockdown. Compared to before lockdown, the contribution of VE particles experienced the largest reduction (by 14.9%), whereas the contributions of BB and CE particles increased by 7.0% and 7.3%, respectively, during the lockdown period. Regional transmission was critical for pollution formation before lockdown, whereas the pollution that occurred during the lockdown period was caused mainly by locally emitted particles (such as VE, CE and BB particles). Weighted potential source contribution function (WPSCF) analysis further verified and emphasized the difference in the contribution of regional transmission for pollution formation before and during lockdown. In addition, the potential source area and intensity of the particles emitted from different sources or formation mechanisms were quite different.
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Affiliation(s)
- Junke Zhang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Huan Li
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Luyao Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
| | - Xiaojuan Huang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China
| | - Wei Zhang
- Sichuan Environmental Monitoring Center, Chengdu, 610074, China
| | - Rui Zhao
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 611756, China
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Li X, Hussain SA, Sobri S, Md Said MS. Overviewing the air quality models on air pollution in Sichuan Basin, China. CHEMOSPHERE 2021; 271:129502. [PMID: 33465622 DOI: 10.1016/j.chemosphere.2020.129502] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/27/2020] [Accepted: 12/29/2020] [Indexed: 06/12/2023]
Abstract
Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some1inspirations for air pollution forecast in other countries with complex terrain.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400, UPM, Serdang, Selangor, Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400, UPM, Serdang, Selangor, Malaysia.
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400, UPM, Serdang, Selangor, Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400, UPM, Serdang, Selangor, Malaysia
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Estimating Ground-Level Particulate Matter in Five Regions of China Using Aerosol Optical Depth. REMOTE SENSING 2020. [DOI: 10.3390/rs12050881] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Aerosol optical depth (AOD) has been widely used to estimate near-surface particulate matter (PM). In this study, ground-measured data from the Campaign on Atmospheric Aerosol Research network of China (CARE-China) and the Aerosol Robotic Network (AERONET) were used to evaluate the accuracy of Visible Infrared Imaging Radiometer Suite (VIIRS) AOD data for different aerosol types. These four aerosol types were from dust, smoke, urban, and uncertain and a fifth “type” was included for unclassified (i.e., total) aerosols. The correlation for dust aerosol was the worst (R2 = 0.15), whereas the correlations for smoke and urban types were better (R2 values of 0.69 and 0.55, respectively). The mixed-effects model was used to estimate the PM2.5 concentrations in Beijing–Tianjin–Hebei (BTH), Sichuan–Chongqing (SC), the Pearl River Delta (PRD), the Yangtze River Delta (YRD), and the Middle Yangtze River (MYR) using the classified aerosol type and unclassified aerosol type methods. The results suggest that the cross validation (CV) of different aerosol types has higher correlation coefficients than that of the unclassified aerosol type. For example, the R2 values for dust, smoke, urban, uncertain, and unclassified aerosol types BTH were 0.76, 0.85, 0.82, 0.82, and 0.78, respectively. Compared with the daily PM2.5 concentrations, the air quality levels estimated using the classified aerosol type method were consistent with ground-measured PM2.5, and the relative error was low (most RE was within ±20%). The classified aerosol type method improved the accuracy of the PM2.5 estimation compared to the unclassified method, although there was an overestimation or underestimation in some regions. The seasonal distribution of PM2.5 was analyzed and the PM2.5 concentrations were high during winter, low during summer, and moderate during spring and autumn. Spatially, the higher PM2.5 concentrations were predominantly distributed in areas of human activity and industrial areas.
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